Truth or truthiness : distinguishing fact from fiction by learning to think like a data scientist /

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Bibliographic Details
Author / Creator:	Wainer, Howard, author.
Imprint:	New York, NY : Cambridge University Press, 2016. ©2016
Description:	xviii, 210 pages ; 24 cm
Language:	English
Subject:	Critical thinking. Inference. Evidence. Belief and doubt. Belief and doubt. Critical thinking. Evidence. Inference.
Format:	Print Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/10505772

Hidden Bibliographic Details
ISBN:	9781107130579 1107130573
Notes:	Includes bibliographical references and index.
Summary:	"Teacher tenure is a problem. Teacher tenure is a solution. Fracking is safe. Fracking causes earthquakes. Our kids are over-tested. Our kids are not tested enough. We read claims like these in the newspaper, often with no justification other than "it feels right." How can we figure out what is right? Escaping from the clutches of truthiness begins with one question: "What's the evidence?" With his usual verve, and disdain for pious nonsense, Howard Wainer offers a refreshing fact-based view of complex problems in altitude of fields, with special emphasis showing in education how to evaluate the evidence, or lack thereof, supporting various kinds of claims. His primary tool is casual inference: how can we convincingly demonstrate the cause of an effect? This wise book is a must-read for anyone who's ever wanted to challenge the pronouncements of authority figures and a captivating narrative that entertains and educates at the same time. Howard Wainer is a Distinguished Research Scientist at the National Board of Medical Examiners. He has published more than 400 articles and chapters in scholarly journals and books. His book Defeating Deception: Escaping the Shackles of Truthiness by Learning to Think like a Data Scientist, will be published by Cambridge University Press in 2016"--

Table of Contents:

Part I. Thinking Like a Data Scientist
1. How the rule of 72 can provide guidance to advance your wealth, your career and your gas mileage
2. Piano virtuosos and the four-minute mile
3. Happiness and causal inference
4. Causal inference and death
5. Using experiments to answer four vexing questions
6. Causal inferences from observational studies: fracking, injection wells, earthquakes, and Oklahoma
7. Life follows art: gaming the missing data algorithm
Part II. Communicating Like a Data Scientist
8. On the crucial role of empathy in the design of communications: genetic testing as an example
9. Improving data displays: the media's, and ours
10. Inside-out plots
11. A century and a half of moral statistics: plotting evidence to affect social policy
Part III. Applying the Tools of Data Science to Education
12. Waiting for Achilles
13. How much is tenure worth?
14. Detecting cheating badly: if it could have been, it must have been
15. When nothing is not zero: a true saga of missing data, adequate yearly progress, and a Memphis charter school
16. Musing about changes in the SAT: is the college board getting rid of the bulldog?
17. For want of a nail: why worthless subscores may be seriously impeding the progress of western civilization

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